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177Lu- prostate specific membrane antigen (PSMA) radio-ligand therapy has been approved abroad for advanced prostate cancer and has been in several clinical trials in China. Based on domestic clinical practice and experimental data and referred to international experience and viewpoints, the expert group forms a consensus on the clinical application of 177Lu-PSMA radio-ligand therapy in prostate cancer to guide clinical practice.

Quality management is a constant and significant concern in enterprises. Effective determination of correct solutions for comprehensive problems helps avoid increased backtesting costs. This study proposes an intelligent quality control method for manufacturing processes based on a human–cyber–physical (HCP) knowledge graph, which is a systematic method that encompasses the following elements: data management and classification based on HCP ternary data, HCP ontology construction, knowledge extraction for constructing an HCP knowledge graph, and comprehensive application of quality control based on HCP knowledge. The proposed method implements case retrieval, automatic analysis, and assisted decision making based on an HCP knowledge graph, enabling quality monitoring, inspection, diagnosis, and maintenance strategies for quality control. In practical applications, the proposed modular and hierarchical HCP ontology exhibits significant superiority in terms of shareability and reusability of the acquired knowledge. Moreover, the HCP knowledge graph deeply integrates the provided HCP data and effectively supports comprehensive decision making. The proposed method was implemented in cases involving an automotive production line and a gear manufacturing process, and the effectiveness of the method was verified by the application system deployed. Furthermore, the proposed method can be extended to other manufacturing process quality control tasks.

Abstract Objectives This study aims to retrospectively analyze the clinical features of Stanford type A acute aortic dissection (TAAAD) based on Sun’s modified classification, and to investigate whether the Sun’s modified classification can be used to assess the risk of preoperative rupture. Methods Clinical data was collected between January 2018 and June 2019. Data included patient demographics, history of disease, type of dissection according to the Sun’s modified classification, time of onset, biochemical tests, and preoperative rupture. Results A total of 387 patients with TAAAD who met the inclusion criteria of Sun’s modified classification were included. There were more complex types, with 75, 151 and 140 patients in the type A1C, A2C and A3C groups, respectively. The age of the entire group of patients was 51.46 ± 12.65 years and 283 (73.1%) were male. The time from onset to the emergency room was 25.37 ± 30.78 h. There were a few cases of TAAAD combined with stroke, pericardial effusion, pleural effusion, and lower extremity and organ ischemia in the complex type group. The white blood cell count (WBC), neutrophil count (NEC) and blood amylase differed significantly between the groups. Three independent risk factors for preoperative rupture were identified: neutrophil count, blood potassium ion level, and platelet count. Binary logistic regression analysis showed that the Sun’s modified classification could not be used to assess the risk of preoperative rupture in TAAAD. Conclusion TAAAD was classified as the complex type in most patients. WBC, NEC and blood amylase were significantly different between the groups. NEC and serum potassium ion level were independent risk factors for preoperative rupture of TAAAD, while platelet count was its protective factor. More samples are needed to determine whether Sun’s modified classification can be used to evaluate the risk of preoperative rupture.

Abstract High-pressure diamond anvil cells have been widely used to create novel states of matter. Nevertheless, the lack of universal in-situ magnetic measurement techniques at megabar pressures makes it difficult to understand the underlying physics of materials’ behavior at extreme conditions, such as high-temperature superconductivity of hydrides and the formation or destruction of the local magnetic moments in magnetic systems. Here, we break through the limitations of pressure on quantum sensors by modulating the uniaxial stress along the nitrogen-vacancy axis and develop the in-situ magnetic detection technique at megabar pressures with high sensitivity ( $$\sim 1{{{\rm{\mu }}}}{{{\rm{T}}}}/\sqrt{{{{\rm{Hz}}}}}$$ ~ 1 μ T / Hz ) and sub-microscale spatial resolution. By directly imaging the magnetic field and the evolution of magnetic domains, we observe the macroscopic magnetic transition of Fe3O4 in the megabar pressure range from ferrimagnetic (α-Fe3O4) to weak ferromagnetic (β-Fe3O4) and finally to paramagnetic (γ-Fe3O4). The scenarios for magnetic changes in Fe3O4 characterized here shed light on the direct magnetic microstructure observation in bulk materials at high pressure and contribute to understanding magnetism evolution in the presence of numerous complex factors such as spin crossover, altered magnetic interactions and structural phase transitions.

Background: Patients with hematological malignancies face an increased risk of developing second primary neoplasms due to various factors, including immune system compromise and chemotherapy-related effects. However, the incidence and associated risk factors in older patients remain poorly understood. This study aimed to assess the incidence, identify risk factors, and evaluate their impact on survival outcomes among older patients with hematological malignancies. Methods: This retrospective single-center study analyzed data from 163 patients, focusing on the occurrence of second primary neoplasms. Cumulative incidence rates were calculated, and risk factor analysis was conducted using a competing risk model. Results: Among 124 eligible patients with a total follow-up duration of 572.57 person-years, the incidence rate of second primary neoplasms was 15.72/1000 person-years. The standardized incidence ratio (SIR) was 0.81 (95% confidence interval [CI] [0.39–1.48], P = 0.518). History of radiotherapy emerged as a significant risk factor (sub-distribution hazard ratio [SHR] = 21.61 [2.81–166.14], P = 0.003), whereas regular natural killer (NK) cell infusion was associated with reduced risk (SHR = 3.25 e−8 [9.81 e−9–1.08 e−7], P ＜ 0.001). Conclusions: These findings underscore the importance of informing older patients with hematological malignancies about the long-term risks of second primary neoplasms. Healthcare providers should carefully weigh risk factors when formulating treatment strategies. The results are valuable for investigating the fundamental principles underlying the occurrence and progression of second primary neoplasms.

Abstract Pyroptosis, a typical inflammatory cell death mode, has been increasingly demonstrated to have therapeutic value in inflammatory diseases such as sepsis. However, the mechanisms and therapeutic targets of sepsis remain elusive. Here, we reported that REGγ inhibition promoted pyroptosis by regulating members of the gasdermin family in macrophages. Mechanistically, REGγ directly degraded Bim, a factor of the Bcl-2 family that can inhibit the cleavage of GSDMD/E, ultimately preventing the occurrence of pyroptosis. Furthermore, cecal ligation and puncture (CLP)-induced sepsis model mice showed downregulation of REGγ at both the RNA and protein levels. Gasdermin-mediated pyroptosis was augmented in REGγ-knockout mice, and these mice exhibited more severe sepsis-related tissue injury. More importantly, we found that REGγ expression was downregulated in clinical sepsis samples, such as those from patients with Pseudomonas aeruginosa (PA) infection. Finally, PA-infected mice showed decreased REGγ levels in the lung. In summary, our study reveals that the REGγ-Bim-GSDMD/E pathway is a novel regulatory mechanism of pyroptosis in sepsis-related tissue injury.

Abstract Background Oral mucositis (OM) is a prevalent and painful complication in patients undergoing anticancer treatment, which significantly impacts patients’ quality of life (QoL) and adherence to therapy. The use of oral probiotics as a preventive strategy for OM has shown promise, but the clinical evidence remains inconclusive. This meta-analysis of randomized controlled trials (RCTs) aims to evaluate the efficacy of probiotics in preventing OM caused by radiotherapy and/or chemotherapy. Methods A comprehensive search of PubMed, EMBASE, Web of Science, Cochrane Library, and ClinicalTrials.gov was conducted up to January 31, 2024, to identify eligible RCTs. The primary outcomes were the incidences of severe OM and all-grade OM. Secondary outcomes included rates of anticancer treatment completion, clinical response, requirement for enteral nutrition, time course of OM, body weight loss, QoL, and adverse events (AEs). Risk ratios (RRs) with 95% confidence intervals (CIs) were calculated. Results A total of 12 RCTs involving 1,376 patients were included in the quantitative analysis. Probiotics administration significantly reduced the risk of severe OM (RR = 0.61, 95%CI: 0.53–0.72, P

High purity and ultrafine DAAF (u-DAAF) is an emerging insensitive charge in initiators. Although there are many ways to obtain u-DAAF, developing a preparation method with stable operation, accurate control, good quality consistency, equipment miniaturization, and minimum manpower is an inevitable requirement to adapt to the current social technology development trend. Here reported is the microfluidic preparation of u-DAAF with tunable particle size by a passive swirling microreactor. Under the guidance of recrystallization growth kinetics and mixing behavior of fluids in the swirling microreactor, the key parameters (liquid flow rate, explosive concentration and crystallization temperature) were screened and optimized through screening experiments. Under the condition that no surfactant is added and only experimental parameters are controlled, the particle size of recrystallized DAAF can be adjusted from 98 nm to 785 nm, and the corresponding specific surface area is 8.45 m2·g−1 to 1.33 m2·g−1. In addition, the preparation method has good batch stability, high yield (90.8%–92.6%) and high purity (99.0%–99.4%), indicating a high practical application potential. Electric explosion derived flyer initiation tests demonstrate that the u-DAAF shows an initiation sensitivity much lower than that of the raw DAAF, and comparable to that of the refined DAAF by conventional spraying crystallization method. This study provides an efficient method to fabricate u-DAAF with narrow particle size distribution and high reproducibility as well as a theoretical reference for fabrication of other ultrafine explosives.

Abstract Moyamoya disease, characterized by basal cerebral artery obstruction, was studied for differential protein expression to elucidate its pathogenesis. Proteomic analysis of cerebrospinal fluid from 10 patients, categorized by postoperative angiography into good and poor prognosis groups, revealed 46 differentially expressed proteins. Notably, cadherin 18 (CDH18) was the most significantly upregulated in the good prognosis group. In addition, the expression of cadherin 18 (CDH18) and phenotypic transformation-related proteins were measured by qRT-PCR and western blot. The effects of CDH18 in vascular smooth muscle cells were detected by CCK-8, EdU, transwell and wound healing assays. The overexpression of CDH18 in vascular smooth muscle cells (VSMCs) was found to inhibit proliferation, migration, and phenotypic transformation. These findings suggest CDH18 as a potential therapeutic target in moyamoya disease.

Abstract Fine-grained management of rice fields can enhance the yield and quality of rice crops. Challenges in achieving fine classification include interference from similar vegetation, the irregularity of natural field shapes, and complex scale variations. This paper introduces Rice Attention Cascade Network (RACNet), for the fine classification of rice fields in high-resolution satellite remote sensing imagery. The network employs the Hybrid Task Cascade network as the base framework and uses spectral and indices mixed multimodal data as input to reinforce the feature differentiation of similar vegetation. Initially, a Channel Attention Deformable-ResNet (CAD-ResNet) was designed to enhance the feature representation of rice on different channels. Deformable convolution improves the ability of CAD-ResNet to capture irregular field shapes. Then, to address the issue of complex scale changes, the multi-scale features extracted by the CAD-ResNet are progressively fused using an Asymptotic Feature Pyramid, reducing the loss of scale information between non-adjacent layers. Experiments on the Meishan rice dataset show that the proposed method is capable of accurate instance segmentation for fragmented or irregularly shaped rice fields. The evaluation metric AP50 of RACNet reaches 50.8%.

Abstract We investigate the precessing motion around the the regular black hole with an asymptotically Minkowski core which has a suppression parameter $$\ell $$ ℓ . We obtain the third-order post-Newtonian quasi-Keplerian motion of a test particle in this spacetime and find its relativistic periastron advance. Then, we test this model with the precessing motion of the star S2 and of OJ 287 and determine the upper limits of the dimensionless suppression parameter as $$\ell /m \sim 10^{-3}$$ ℓ / m ∼ 10 - 3 , where m is the mass of the black hole. Compared with the bound given by the shadow of Sgr A*, our bound on $$\ell /m$$ ℓ / m is reduced by 2 orders of magnitude, although our upper limit of $$\ell $$ ℓ still needs further improvement.

The development of pipeline steels with exceptional cryogenic toughness is deemed imperative for their applications in various engineering fields. In this work, API X65 steel with lamellar grain (LG) structure is constructed through warm deformation techniques. Comparative analysis with raw API X65 steel revealed notable enhancements in both yield strength (YS) and ultimate strength (UTS), exhibiting increments of 315 MPa and 164 MPa, respectively, while retaining substantial fracture toughness (KIc = 251.14 MPa m0.5). Remarkably, the LG steel exhibits a distinct absence of a ductile-brittle transition behavior over a wide temperature range, maintaining an exceptionally high impact energy from room temperature (RT) to liquid nitrogen temperature (LNT), and the Charpy impact energy exceeding 330 J at LNT, nearly 16 times higher than the raw API X65 steel. This performance can be primarily attributed to the superior plastic deformation capability, coupled with the delamination toughening mechanism. The resultant tortuous path of crack propagation effectively facilitates the absorption of substantial energy, decreases notch tip sensitivity depending on the temperature, stress triaxiality, and strain rate, thereby fostering excellent cryogenic toughness.

In patients with Alzheimer’s disease, gamma-glutamyl transferase 5 (GGT5) expression has been observed to be downregulated in cerebrovascular endothelial cells. However, the functional role of GGT5 in the development of Alzheimer’s disease remains unclear. This study aimed to explore the effect of GGT5 on cognitive function and brain pathology in an APP/PS1 mouse model of Alzheimer’s disease, as well as the underlying mechanism. We observed a significant reduction in GGT5 expression in two in vitro models of Alzheimer’s disease (Aβ1–42–treated hCMEC/D3 and bEnd.3 cells), as well as in the APP/PS1 mouse model. Additionally, injection of APP/PS1 mice with an adeno-associated virus encoding GGT5 enhanced hippocampal synaptic plasticity and mitigated cognitive deficits. Interestingly, increasing GGT5 expression in cerebrovascular endothelial cells reduced levels of both soluble and insoluble amyloid-β in the brains of APP/PS1 mice. This effect may be attributable to inhibition of the expression of β-site APP cleaving enzyme 1, which is mediated by nuclear factor-kappa B. Our findings demonstrate that GGT5 expression in cerebrovascular endothelial cells is inversely associated with Alzheimer’s disease pathogenesis, and that GGT5 upregulation mitigates cognitive deficits in APP/PS1 mice. These findings suggest that GGT5 expression in cerebrovascular endothelial cells is a potential therapeutic target and biomarker for Alzheimer’s disease.

Disperse ferrite is generally embedded in lightweight steel, yet exhibits decent performance, thereby prompting a question: can heterogeneous design optimize it? Here, two representative structures, featured with discontinuous fibrous and dispersed ferrite separately embedded in the austenite matrix, were constructed as examples to address the issue. A heterostructure with fibrous ferrite shows a remarkable product (49 GPa·%) of ultimate strength and total elongation, standing out among other lightweight steels. Superior strength-ductility synergy is primarily attributed to hetero-deformation-induced strengthening and hardening. Abundant hetero-interactions imparted by phase boundaries, dense slip bands in austenite and dislocation networks inside ferrite serve as underlying physical mechanisms.

Heterostructured ferritic steels with bimodal-grained lamellar (BG-L) and ultrafine-grained lamellar (UFG-L) microstructure were prepared through a warm deformation process. The BG-L steel exhibits enhanced mechanical properties compared to conventional quenched and tempered (QT) steel. While the UFG-L steel demonstrates an outstanding combination of strength, ductility, and toughness. Furthermore, the UFG-L steels exhibit no ductile-to-brittle transition (DBT) from room temperature (RT) to liquid nitrogen temperature (LNT) and the Charpy impact energy remains as high as 314 J at LNT. The enhanced toughness at LNT can be attributed to the crack-arrester mechanism caused by grain-boundary delamination.

Global energy and environmental issues are becoming increasingly problematic, and the vibration and noise problem of 110 kV transformers, which are the most widely distributed, have attracted widespread attention from both inside and outside the industry. DC bias is one of the main contributing factors to vibration noise during the normal operation of transformers. To clarify the vibration and noise mechanism of a 110 kV transformer under a DC bias, a multi-field coupling model of a 110 kV transformer was established using the finite element method. The electromagnetic, vibration, and noise characteristics during the DC bias process were compared and quantified through field circuit coupling in parallel with the power frequency of AC, harmonic, and DC power sources. It was found that a DC bias can cause significant distortions in the magnetic flux density, force, and displacement distributions of the core and winding. The contributions of the DC bias effect to the core and winding are different at Kdc = 0.85. At this point, the core approached saturation, and the increase in the core force and displacement slowed. However, the saturation of the core increased the leakage flux, and the stress and displacement of the winding increased faster. The sound field distribution characteristics of the 110 kV transformer under a DC bias are related to the force characteristics. When the DC bias coefficient was 1.25, the noise sound pressure level reached 73.6 dB.

Abstract While KRAS mutation is the leading cause of low survival rates in lung cancer bone metastasis patients, effective treatments are still lacking. Here, we identified homeobox C10 (HOXC10) as a lynchpin in pan-KRAS-mutant lung cancer bone metastasis. Through RNA-seq approach and patient tissue studies, we demonstrated that HOXC10 expression was dramatically increased. Genetic depletion of HOXC10 preferentially impeded cell proliferation and migration in vitro. The bioluminescence imaging and micro-CT results demonstrated that inhibition of HOXC10 significantly reduced bone metastasis of KRAS-mutant lung cancer in vivo. Mechanistically, the transcription factor HOXC10 activated NOD1/ERK signaling pathway to reprogram epithelial-mesenchymal transition (EMT) and bone microenvironment by activating the NOD1 promoter. Strikingly, inhibition of HOXC10 in combination with STAT3 inhibitor was effective against KRAS-mutant lung cancer bone metastasis by triggering ferroptosis. Taken together, these findings reveal that HOXC10 effectively alleviates pan-KRAS-mutant lung cancer with bone metastasis in the NOD1/ERK axis-dependent manner, and support further development of an effective combinatorial strategy for this kind of disease.

Abstract Heterogeneous thermocatalysis of formic acid dehydrogenation by metals in solution is of great importance for chemical storage and production of hydrogen. Insightful understanding of the complicated formic acid dehydrogenation kinetics at the metal-solution interface is challenging and yet essential for the design of efficient heterogeneous formic acid dehydrogenation systems. In this work, formic acid dehydrogenation kinetics is initially studied from a perspective of electrochemistry by decoupling this reaction on Pd catalyst into two short-circuit half reactions, formic acid oxidation reaction and hydrogen evolution reaction and manipulating the electrical double layer impact from the solution side. The pH-dependences of formic acid dehydrogenation kinetics and the associated cation effect are attributed to the induced change of electric double layer structure and potential by means of electrochemical measurements involving kinetic isotope effect, in situ infrared spectroscopy as well as grand canonical quantum mechanics calculations. This work showcases how kinetic puzzles on some important heterogeneous catalytic reactions can be tackled by electrochemical theories and methodologies.

Abstract Hyperuricemia, characterized by elevated levels of serum uric acid (SUA), is linked to a spectrum of commodities such as gout, cardiovascular diseases, renal disorders, metabolic syndrome, and diabetes, etc. Significantly impairing the quality of life for those affected, the prevalence of hyperuricemia is an upward trend globally, especially in most developed countries. UA possesses a multifaceted role, such as antioxidant, pro-oxidative, pro-inflammatory, nitric oxide modulating, anti-aging, and immune effects, which are significant in both physiological and pathological contexts. The equilibrium of circulating urate levels hinges on the interplay between production and excretion, a delicate balance orchestrated by urate transporter functions across various epithelial tissues and cell types. While existing research has identified hyperuricemia involvement in numerous biological processes and signaling pathways, the precise mechanisms connecting elevated UA levels to disease etiology remain to be fully elucidated. In addition, the influence of genetic susceptibilities and environmental determinants on hyperuricemia calls for a detailed and nuanced examination. This review compiles data from global epidemiological studies and clinical practices, exploring the physiological processes and the genetic foundations of urate transporters in depth. Furthermore, we uncover the complex mechanisms by which the UA induced inflammation influences metabolic processes in individuals with hyperuricemia and the association with its relative disease, offering a foundation for innovative therapeutic approaches and advanced pharmacological strategies.

To study the internal deformation evolution law of soil mass corresponding to subsidence stretching area of mining areas with thick loose layer, the No.10111-working face of Suntuan coal mine in Huaibei is selected, and No.1—3 vertical boreholes are arranged at 60 m spacing along the direction perpendicular to the advancing direction from the near to the distant for the loose layer corresponding to stretching area of the working face. In the process of coal mining subsidence, the borehole deformation monitoring is carried out based on the technology of optical fiber (borehole No.1) and inclinometer (borehole No.2—3). The area occupied by the overlying rock strata and loose layers mobilized by coal mining is considered as a deformation zone, and the concept of the movement angle of strata of arbitrary thickness is introduced. The results show that: The maximum depth at which strain occurs in the borehole No.1 is about 157 meters, with the deeper sections of the borehole reaching the active phase before the shallower; Within the monitoring range of boreholes No.2 and No.3, the geological formations can be divided from bottom to top into stable sections, lower, middle, and upper sections of the deformation zone. The final cumulative horizontal displacement at the borehole openings of No.2 and No.3 is 129.8 mm and 99.4 mm respectively, and the maximum displacement depths of about 108 m and 75 m respectively; Moreover, the horizontal displacement distribution of No.2 and No.3 borehole from bottom to top is generally uniform, and the average horizontal displacement per meter borehole is about 1.2 mm and 1.3 mm, respectively; In each borehole, the lower part of the deformation zone reaches the active period before the upper part and the upper part still has weak deformation after the lower part of the deformation zone is stable; For a certain thickness of strata in the loose layer, the movement angle increases with the increase of its depth, and the depth h of the lower boundary of the loose layer deformation zone decreases with the increase of the horizontal distance l from the working face, which accords with the exponential function relationship.

Integrase strand transfer inhibitors (INSTIs) have emerged as the first-line choice for treating human immunodeficiency virus (HIV) infection due to their superior efficacy and safety. However, the impact of INSTIs on the development of neuropsychiatric conditions in people living with HIV (PLWH) is not fully understood due to limited data. In this study, we conducted a cross-sectional examination of PLWH receiving antiretroviral therapy, with a specific focus on HIV-positive men who have sex with men (MSM) on INSTI-based regimens (n = 61) and efavirenz (EFV)-based regimens (n = 28). Participants underwent comprehensive neuropsychiatric evaluations and multimodal magnetic resonance imaging (MRI) scans, including T1-weighted images and resting-state functional MRI. Compared to the EFV group, the INSTI group exhibited primarily reduced gray matter volume (GMV) in the right superior parietal gyrus, higher regional homogeneity (ReHo) in the left postcentral gyrus, lower ReHo in the right orbital part of the inferior frontal gyrus, and increased voxel-wise functional connectivity for the seed region in the left inferior temporal gyrus with clusters in the right cuneus. Furthermore, the analysis revealed a main effect of antiretroviral drugs on GMV changes, but no main effect of neuropsychiatric disorders or their interaction. The repeated analysis of participants who did not switch regimens confirmed the GMV changes in the INSTI group, validating the initial findings. Our study demonstrated gray matter atrophy and functional brain changes in PLWH on INSTI-based regimens compared to those on EFV-based regimens. These neuroimaging results provide valuable insights into the characteristics of brain network modifications in PLWH receiving INSTI-based regimens.

Abstract Focal segmental glomerulosclerosis (FSGS), a clinicopathological condition characterized by nephrotic-range proteinuria, has a high risk of progression to end-stage renal disease (ESRD). Meanwhile, the recurrence of FSGS after renal transplantation is one of the main causes of graft loss. The diagnosis of recurrent FSGS is mainly based on renal puncture biopsy transplants, an approach not widely consented by patients with early mild disease. Therefore, there is an urgent need to find definitive diagnostic markers that can act as a target for early diagnosis and intervention in the treatment of patients. In this review, we summarize the domestic and international studies on the pathophysiology, pathogenesis and earliest screening methods of FSGS and describe the functions and roles of specific circulating factors in the progression of early FSGS, in order to provide a new theoretical basis for early diagnosis of FSGS recurrence, as well as aid the exploration of therapeutic targets.

Abstract Background The relationship between thyroid hormone (TH) levels in vivo and osteoarthritis (OA) remains inconclusive. This study aims to investigate the association between TH levels and OA, analyze the effect of triiodothyronine on hypertrophic chondrocyte differentiation and OA progression, and identify potential target genes of triiodothyronine in OA to evaluate its diagnostic value. Methods Two-sample mendelian randomization method was used to probe the causal links between hyperthyroidism and OA. Differentially expressed genes (DEGs) from two RNA-sequencing data in Gene Expression Omnibus (GSE199847 and GSE114007) and enrichment analysis of DEGs (166 commonly upregulated genes and 71 commonly downregulated genes of GSE199847 and GSE114007) was performed to analyze the effect of triiodothyronine (T3) on hypertrophic chondrocyte differentiation and OA. C28/I2 cells treated with T3 and reverse transcription and quantitative real-time polymerase chain reaction were used to validate T3 targeted genes. The diagnostic performance of target genes was assessed by the receiver operating characteristic (ROC) curve and area under the curve (AUC). Results There was a positive causal association between hyperthyroidism and OA (IVW result, OR = 1.330, 95% CI 1.136–1.557, P = 0.0004). Weighted median and Weighted mode analysis also demonstrated that hyperthyroidism had a positive causal association with OA (p 1). Bioinformatics analysis indicated T3 can partially induce the emergence of late hypertrophic chondrocyte and promote OA through extracellular matrix organization, blood vessel development, skeletal system development and ossification. Post-T3 treatment, MAFB, C1QTNF1, COL3A1 and ANGPTL2 were significantly elevated in C28/I2 cells. ROC curves in GSE114007 showed that AUC of all above genes were ≥ 0.7. Conclusions This study identified that hyperthyroidism has a positive causal association with OA by MR analysis. T3 induced hypertrophic chondrocytes promote OA progression by upregulating genes such as MAFB, C1QTNF1, COL3A1 and ANGPTL2, which can also serve as OA diagnosis.

Abstract Background Conventional single-energy CT can only provide a raw estimation of electron density (ED) for dose calculation by developing a calibration curve that simply maps the HU values to ED values through their correlations. Spectral CT, also known as dual-energy CT (DECT) or multi-energy CT, can generate a series of quantitative maps, such as ED maps. Using spectral CT for radiotherapy simulations can directly acquire ED information without developing specific calibration curves. The purpose of this study is to assess the feasibility of utilizing electron density (ED) maps generated by a novel dual-layer detector spectral CT simulator for dose calculation in radiotherapy treatment plans. Methods 30 patients from head&neck, chest, and pelvic treatment sites were selected retrospectively, and all of them underwent spectral CT simulation. Treatment plans based on conventional CT images were transplanted to ED maps with the same structure set, including planning target volume (PTV) and organs at risk (OARs), and the dose distributions were then recalculated. The differences in dose and volume histogram (DVH) parameters of the PTV and OARs between the two types of plans were analyzed and compared. Besides, gamma analysis between these plans was performed by using MEPHYSTO Navigator software. Results In terms of PTV, the homogeneity index (HI), gradient index (GI), D2%, D98%, and Dmean showed no significant difference between conventional plans and ED plans. For OARs, statistically significant differences were observed in parotids D50%, brainstem in head&neck plans, spinal cord in chest plans and rectum D50% in pelvic plans, whereas the variance remained minor. For the rest, the DVH parameters exhibited no significant difference between conventional plans and ED plans. All of the mean gamma passing rates (GPRs) of gamma analysis were higher than 90%. Conclusion Compared to conventional treatment plans relying on CT images, plans utilizing ED maps demonstrated similar dosimetric quality. However, the latter approach enables direct utilization in dose calculation without the requirements of establishing and selecting a specific Hounsfield unit (HU) to ED calibration curve, providing an advantage in clinical applications.

Abstract Motivation Retrosynthesis planning poses a formidable challenge in the organic chemical industry, particularly in pharmaceuticals. Single-step retrosynthesis prediction, a crucial step in the planning process, has witnessed a surge in interest in recent years due to advancements in AI for science. Various deep learning-based methods have been proposed for this task in recent years, incorporating diverse levels of additional chemical knowledge dependency. Results This paper introduces UAlign, a template-free graph-to-sequence pipeline for retrosynthesis prediction. By combining graph neural networks and Transformers, our method can more effectively leverage the inherent graph structure of molecules. Based on the fact that the majority of molecule structures remain unchanged during a chemical reaction, we propose a simple yet effective SMILES alignment technique to facilitate the reuse of unchanged structures for reactant generation. Extensive experiments show that our method substantially outperforms state-of-the-art template-free and semi-template-based approaches. Importantly, our template-free method achieves effectiveness comparable to, or even surpasses, established powerful template-based methods. Scientific contribution We present a novel graph-to-sequence template-free retrosynthesis prediction pipeline that overcomes the limitations of Transformer-based methods in molecular representation learning and insufficient utilization of chemical information. We propose an unsupervised learning mechanism for establishing product-atom correspondence with reactant SMILES tokens, achieving even better results than supervised SMILES alignment methods. Extensive experiments demonstrate that UAlign significantly outperforms state-of-the-art template-free methods and rivals or surpasses template-based approaches, with up to 5% (top-5) and 5.4% (top-10) increased accuracy over the strongest baseline.

The electricity consumption in the smart grids consists of an uncertainty feature. Also, an unstable atmosphere situation causes photovoltaic (PV) generation will be undefined output. With both of these problems, the net demand power of consumers can’t be a specific value. On the other hand, using consumption patterns, the consumptions and generations could be predicted for improving the operation of the power system. This paper reports the results of the differential performance of probabilistic forecasting of the residential electricity onsumption, PV power generation, and net demand related to smart buildings using the novel method of the Improved Deep Mixture Density Network (IDMDN). According to this, investigators used a strong Multi to Multi (M2M) mapping of the neural network model. They followed that they had used a kind of beta kernel to decrease the number of leakage issues. It is an attempt to generate random predictions by the method of end-to-end. It expressed a new performance of changed initiation and multiple procedures of educating to decrease or remove unsteady traits in the probabilistic problems of the beta kernel function. The results show good performance of the proposed method in comparison with other methods.

Abstract Background The effectiveness of robot-assisted surgery remains contentious due to the lack of high-quality randomized controlled trials (RCTs) to elevate the level of evidence. We aimed to evaluate the postoperative radiographic outcomes of robot-assisted (RAS-THA) versus manual (M-THA) total hip arthroplasty. Methods This multicenter RCT was performed from March 1, 2021 to December 1, 2021. Patients were randomly assigned to routine M-THA or to RAS-THA that used the TRex-RS orthopedic joint surgical navigation system. The primary outcome was to compare the acetabular component orientation, femoral stem alignment, femoral canal fill ratio, and leg length discrepancy between RAS-THA and M-THA using postoperative radiography. Subgroup analyses of the two groups stratified by surgical approach, gender, and BMI were also conducted. Results Seventy-three participants were randomly allocated to the RAS-THA group, while seventy-two participants were assigned to the M-THA group. Compared to the M-THA group, the RAS-THA group exhibited less variability in the preoperative planning of the vertical center of rotation (VCOR; P 0.05) between the two groups. Further subgroup analysis also showed that the RAS-THA group had fewer horizontal center of rotation (HCOR) and leg length differences when stratified by surgical approach, gender, and overweight status. Conclusion This RCT found that, regardless of the surgical approach, gender, or body mass index, RAS-THA can effectively improve the postoperative VCOR and significantly reduce the variability of leg length difference. RAS-THA should be considered an effective method to enhance surgical precision by achieving less variability in challenging patients with leg length discrepancies. Trial registration: ChiCTR2100044124.

The surgical navigation system enhances surgical safety and accuracy by providing precise guidance. However, traditional pose estimation algorithms lack real-time performance and accuracy. To address this issue, a multi-average Long Short Term Memory (LSTM) prediction network is designed to maintain sensitivity in estimating the position of surgical instruments and track their random motion trends. Additionally, the spatial coordinates of positioning markers are applied back to the imaging plane, reducing the recognition range and improving algorithm running speed. Experimental results show that the average time of estimation is less than 1ms while ensuring the prediction effect.

Abstract C-1 Glycals serve as pivotal intermediates in synthesizing diverse C-glycosyl compounds and natural products, necessitating the development of concise, efficient and user-friendly methods to obtain C-1 glycosides is essential. The Suzuki-Miyaura cross-coupling of glycal boronates is notable for its reliability and non-toxic nature, but glycal donor stability remains a challenge. Herein, we achieve a significant breakthrough by developing stable glycal boronates, effectively overcoming the stability issue in glycal-based Suzuki–Miyaura coupling. Leveraging the balanced reactivity and stability of our glycal boronates, we establish a robust palladium-catalyzed glycal-based Suzuki-Miyaura reaction, facilitating the formation of various C(sp 2)-C(sp), C(sp 2)-C(sp 2 ), and C(sp 2)-C(sp 3) bonds under mild conditions. Notably, we expand upon this achievement by developing the DNA-compatible glycal-based cross-coupling reaction to synthesize various glycal-DNA conjugates. With its excellent reaction reactivity, stability, generality, and ease of handling, the method holds promise for widespread appication in the preparation of C-glycosyl compounds and natural products.

Abstract Background Analyzing distance-dependent functional connectivity density (FCD) yields valuable insights into patterns of brain activity. Nevertheless, whether alterations of FCD in non-acute stroke patients are associated with the anatomical distance between brain regions remains unclear. This study aimed to explore the distance-related functional reorganization in non-acute stroke patients following left and right hemisphere subcortical lesions, and its relationship with clinical assessments. Methods In this study, we used resting-state fMRI to calculate distance-dependent (i.e., short- and long-range) FCD in 25 left subcortical stroke (LSS) patients, 22 right subcortical stroke (RSS) patients, and 39 well-matched healthy controls (HCs). Then, we compared FCD differences among the three groups and assessed the correlation between FCD alterations and paralyzed motor function using linear regression analysis. Results Our findings demonstrated that the left inferior frontal gyrus displayed distance-independent FCD changes, while the bilateral supplementary motor area, cerebellum, and left middle occipital gyrus exhibited distance-dependent FCD alterations in two patient subgroups compared with HCs. Furthermore, we observed a positive correlation between increased FCD in the bilateral supplementary motor area and the motor function of lower limbs, and a negative correlation between increased FCD in the left inferior frontal gyrus and the motor function of both upper and lower limbs across all stroke patients. These associations were validated by using a longitudinal dataset. Conclusions The FCD in the cerebral and cerebellar cortices shows distance-related changes in non-acute stroke patients with motor dysfunction, which may serve as potential biomarkers for predicting motor outcomes after stroke. These findings enhance our comprehension of the neurobiological mechanisms driving non-acute stroke. Trial registration All data used in the present study were obtained from a research trial registered with the ClinicalTrials.gov database (NCT05648552, registered 05 December 2022, starting from 01 January 2022).

Abstract Background This paper attempted to clarify the role and mechanism of vacuolar protein sorting-associated protein 72 homolog (VPS72) in the progression of prostate cancer (PCa). Methods Clinical information and gene expression profiles of patients with prostate cancer were obtained from The Cancer Genome Atlas (TCGA). VPS72 expression in PCa and the potential mechanism by which VPS72 affects PCa progression was investigated. Next, we performed COX regression analysis to identify the independent prognostic factors of PCa, and constructed a nomogram. The sensitivity of chemotherapeutic medications was anticipated using “pRRophetic”. Subsequently, in vitro assays to validate the effect of VPS72 on PCa cell proliferation, migration and susceptibility to anti-androgen therapy. Results The expression of VPS72 was considerably higher in PCa tissues compared to normal tissues. Significant correlations were found between high VPS72 expression and a poor prognosis and adverse clinicopathological factors. The nomogram model constructed based on VPS72 expression has good predictive performance. According to GSEA, VPS72-related genes were enriched in the NF-kB pathways, cytokine-cytokine receptor interaction and chemokine signaling pathway in PCa. Although PCa with low VPS72 expression was more adaptable to chemotherapeutic medications, our in vitro experiment showed that VPS72 knockdown significantly decreased the PCa cell migration, proliferation, and resistance to anti-androgen therapy. Conclusions In summary our findings suggests that VPS72 could play a crucial role in the malignant progression of PCa, and its expression level can be employed as a possible biomarker of PCa prognosis.

Glucose oxidase (GOD) has been investigated as a potential additive for enhancing intestinal health and growth performance in poultry. However, limited research exists on the effects of ultra-high doses of GOD in practical poultry production. This study aimed to investigate the impact of high dietary GOD levels on broiler growth performance, antioxidant capacity, and intestinal microbiota. A total of 400 healthy, 1-day-old, slow-growing broiler chickens were randomly assigned to four treatment groups. The control group was fed a standard basal diet, while the other groups (G1, G2, and G3) were fed the basal diet supplemented with 4 U/g, 20 U/g, and 100 U/g of VTR GOD, respectively. The results showed that a dose of 100 U/g GOD significantly improved the final body weight and average daily feed intake (ADFI) (p

IntroductionMental health is the cornerstone of public health, especially where middle-aged and older adults during the COVID-19 pandemic were concerned. The impact of Internet usage on mental health in the time of the crisis still presents a mixed picture.MethodsThis study employs the PSM-DID method according to longitudinal data (CFPS) to explore whether Internet usage reduced the impact of COVID-19 on the mental health of middle-aged and older adults.ResultsThe results reveal that Internet use improves the mental health of middle-aged and older adults during the pandemic in China, but that the impact varies between urban and rural residents. Furthermore, the moderator effects model shows that people’s perceptions of the Internet have an impact upon the length of time spent online and its consequent effect on mental health.DiscussionThese findings suggested that Internet use had a significant effect on alleviating the levels of depression in middle-aged and older adults. Greater marginal gains may be realized by enhancing the digital capacity of and narrowing the digital divide that exists among rural residents. The enhancement of digital capacity and proper guidance in digital education should be taken into consideration where the mental health of middle-aged and older adults is at issue.

The objective of this investigation was to assess the prognostic significance of the comprehensive malnutritional index (CNI) in patients with locally advanced rectal cancer (LARC) who underwent neoadjuvant chemoradiotherapy (nCRT) followed by surgery. A total of 240 LARC patients were recruited. The CNI was calculated using principal components analysis based on hemoglobin (Hb), total lymphocyte count (TLC), albumin (ALB), body mass index (BMI), and usual body weight percentage (UBW%). The patients were then categorized into two groups based on the median CNI value. Cox regression and survival analyses were performed. The CNI-low (120 cases) and CNI-high (120 cases) groups were classified based on the median CNI value. The results indicated that the CNI demonstrated superior predictive ability for disease-free survival (DFS) and overall survival (OS) compared to other malnutritional indexes. LARC patients in the CNI-high group had significantly longer DFS and OS compared to those in the CNI-low group. Multivariate analysis revealed that the CNI was an independent prognostic factor for DFS (hazard ratio [HR] = 0.49; 95% confidence interval[CI], 0.29–0.83; P = 0.008) and OS (HR = 0.30; 95% CI, 0.16-0.58; P < 0.001). Additionally, the CNI-high group benefited from postoperative chemotherapy (DFS: P = 0.029, OS: P = 0.024), while the CNI-low group did not show such benefits (DFS: P = 0.448, OS: P = 0.468). These findings suggest that the CNI could serve as a valuable prognostic indicator for LARC patients who undergo nCRT followed by surgery. Preoperative nutrition optimization is important for LARC patients.

ABSTRACT To investigate the impact of Small Intestinal Bacterial Overgrowth (SIBO) on the efficacy of Fecal Microbiota Transplantation (FMT) in patients with chronic constipation, our research team included 218 patients with chronic constipation treated with FMT. Based on the results of the SIBO breath test, the patients were divided into two groups: the constipation with SIBO group (SIBO) and the constipation without SIBO group (non-SIBO). The efficacy of the two groups was evaluated using constipation-related scoring scales. At the same time, feces and small intestinal fluid samples were collected from both groups before and after FMT to compare the changes in the intestinal microbiota through 16S rRNA sequencing. In this study, it was found that the clinical efficacy of FMT in the SIBO group was superior to that in the non-SIBO group. After FMT treatment, both groups showed a significant increase in bowel frequency and improvement in stool characteristics. Abdominal symptoms, rectal symptoms, and defecation symptoms were significantly alleviated (P < 0.05), and patients’ quality of life was significantly enhanced (P < 0.05). After FMT, except for the Constipation Assessment Scale scores, other scale scores showed significant differences between the two groups, the SIBO group scoring significantly better than the non-SIBO group (P < 0.05). After FMT, there were minor changes in the colonic microbiota but more substantial changes in the small intestinal microbiota. At baseline, the SIBO group had a higher abundance of Veillonella, and lower abundances of Escherichia-Shigella and Acinetobacter compared to the non-SIBO group. Chronic constipation patients with SIBO have a better response to FMT than those without SIBO.IMPORTANCEExisting studies have rarely considered the impact of the small intestine’s microbial state on the efficacy of fecal microbiota transplantation (FMT), nor have they extensively explored the effect of the small intestine’s microbial state on the recovery of colonic motility. Therefore, this study investigates the influence of small intestinal bacterial overgrowth (SIBO) on the efficacy of FMT in treating constipation, specifically the impact of the microbial state of the small intestine on the restoration of colonic homeostasis, and consequently on the recovery of colonic motility.

BackgroundIndividuals with substance use disorder (SUD) are characterized by loss of control in drug use, such as increased impulsivity. Methamphetamine and methcathinone are psychostimulants, the use of which is accompanied by a high level of impulsivity. Whether individuals with methamphetamine use disorder (MUD) and methcathinone use disorder (MCUD) differ in different aspects of impulsivity is unclear.MethodsWe investigated impulsivity traits and behaviors in individuals with MUD and MCUD. The Barratt Impulsiveness Scale (BIS), Sensation Seeking Scale (SSS), and delay discounting task (DDT) were assessed in individuals with MUD and MCUD and in healthy controls (HCs); then, we performed network-based analysis and computational modeling to understand the potential differences among the three groups.ResultsMUD subjects scored higher than MCUD subjects in terms of motor impulsivity, nonplanning impulsivity, and total BIS scores. The network analysis revealed that there were no significant differences between MUD and MCUD subjects in any centrality indices. The discount rate of MUD and MCUD subjects was significantly greater than that of HCs, whereas there was no difference in the discount rate between the two addiction groups.ConclusionsThese findings suggest that MUD and MCUD participants differ in impulsivity traits but not in impulsive behaviors, implying that impulsive traits and behaviors represent different aspects of impulsivity.

Background: Chronic rhinosinusitis with nasal polyps (CRSwNP) is a prevalent inflammatory disorder affecting the upper respiratory tract. Recent studies have indicated an association between CRSwNP and mitochondrial metabolic disorder characterized by impaired metabolic pathways; however, the precise mechanisms remain unclear. This study aims to investigate the mitochondrial-related signature in individuals diagnosed with CRSwNP. Methods: Through the integration of differentially expressed genes (DEGs) with the mitochondrial gene set, differentially expressed mitochondrial-related genes (DEMRGs) were identified. Subsequently, the hub DEMRGs were selected using 4 integrated machine learning algorithms. Immune and mitochondrial characteristics were estimated based on CIBERSORT and ssGSEA algorithms. Bioinformatic findings were confirmed through RT-qPCR, immunohistochemistry, and ELISA for nasal tissues, as well as Western blotting analysis for human nasal epithelial cells (hNECs). The relationship between hub DEMRGs and disease severity was assessed using Spearman correlation analysis. Results: A total of 24 DEMRGs were screened, most of which exhibited lower expression levels in CRSwNP samples. Five hub DEMRGs (ALDH1L1, BCKDHB, CBR3, HMGCS2, and OXR1) were consistently downregulated in both the discovery and validation cohorts. The hub genes showed a high diagnostic performance and were positively correlated with the infiltration of M2 macrophages and resting mast cells. Experimental results confirmed that the 5 genes were downregulated at both the mRNA and protein levels within nasal polyp tissues. Finally, a significant and inverse relationship was identified between the expression levels of these genes and both the Lund-Mackay and Lund-Kennedy scores. Conclusion: Our findings systematically unraveled 5 hub markers correlated with mitochondrial metabolism and immune cell infiltration in CRSwNP, suggesting their potential to be based to design diagnostic and therapeutic strategies for the disease.

ABSTRACT Objectives: Osteoarthritis (OA) is a degenerative disease associated with chondrocyte injury. This study investigated the dysregulation of microRNA-650 (miR-650) in cartilage tissues of patients with OA. Its function and mechanism were also investigated in OA cell models. Methods: miR-650 levels were examined in 15 OA cartilage tissues and ten healthy cartilage tissues. SW1353 cells were used for cell function experiments and IL-1β was applied to the cells to mimic OA conditions in vitro. Cell functions such as proliferation, apoptosis, and inflammation were detected. The downstream target gene of miR-650 was identified and confirmed by bioinformatic analysis and luciferase activity assay. Rescue experiments were performed to verify the mechanism. Results: Suppressed expression of miR-650 was tested in patients with OA and cell models. Overexpression of miR-650 increased cell proliferation but suppressed apoptosis and inflammation of SW1353. As the target gene of miR-650, WNT1 overexpression counteracted the role of miR-650 in the function of SW1353. Conclusion: miR-650 can protect against articular cartilage injury in OA by targeting WNT1. Level of Evidence I, Experimental Study.

IntroductionNon-alcoholic fatty liver disease (NAFLD) represents a major global health challenge, often undiagnosed because of suboptimal screening tools. Advances in machine learning (ML) offer potential improvements in predictive diagnostics, leveraging complex clinical datasets.MethodsWe utilized a comprehensive dataset from the Dryad database for model development and training and performed external validation using data from the National Health and Nutrition Examination Survey (NHANES) 2017–2020 cycles. Seven distinct ML models were developed and rigorously evaluated. Additionally, we employed the SHapley Additive exPlanations (SHAP) method to enhance the interpretability of the models, allowing for a detailed understanding of how each variable contributes to predictive outcomes.ResultsA total of 14,913 participants were eligible for this study. Among the seven constructed models, the light gradient boosting machine achieved the highest performance, with an area under the receiver operating characteristic curve of 0.90 in the internal validation set and 0.81 in the external NHANES validation cohort. In detailed performance metrics, it maintained an accuracy of 87%, a sensitivity of 92.9%, and an F1 score of 0.92. Key predictive variables identified included alanine aminotransferase, gammaglutamyl transpeptidase, triglyceride glucose–waist circumference, metabolic score for insulin resistance, and HbA1c, which are strongly associated with metabolic dysfunctions integral to NAFLD progression.ConclusionsThe integration of ML with SHAP interpretability provides a robust predictive tool for NAFLD, enhancing the early identification and potential management of the disease. The model’s high accuracy and generalizability across diverse populations highlight its clinical utility, though future enhancements should include longitudinal data and lifestyle factors to refine risk assessments further.

Background: Along with the ageing of society, the absolute prevalence of age-related diseases is expected to rise, leading to a substantial burden on healthcare systems and society. Thus, there is an urgent need to promote healthy ageing. As opposed to chronological age, biological age was introduced to accurately represent the ageing process, as it considers physiological deterioration that is linked to morbidity and mortality risk. Furthermore, biological age responds to various factors, including nutritional factors, which have the potential to mitigate the risk of age-related diseases. As a result, a promising biomarker of biological age known as the epigenetic clock has emerged as a suitable measure to investigate the direct relations between nutritional factors and ageing, thereby identifying potential intervention targets to improve healthy ageing. Methods: In this study, we analysed data from 3,969 postmenopausal women from the Women's Health Initiative to identify nutrients that are associated with the rate of ageing by using an accurate measure of biological age called the PhenoAge epigenetic clock. We used Copula Graphical Models, a data-driven exploratory analysis tool, to identify direct relationships between nutrient intake and age-acceleration, while correcting for every variable in the dataset. Results: We revealed that increased dietary intakes of coumestrol, beta-carotene and arachidic acid were associated with decelerated epigenetic ageing. In contrast, increased intakes of added sugar, gondoic acid, behenic acid, arachidonic acid, vitamin A and ash were associated with accelerated epigenetic ageing in postmenopausal women. Conclusion: Our study discovered direct relations between nutrients and epigenetic ageing, revealing promising areas for follow-up studies to determine the magnitude and causality of our estimated diet-epigenetic relationships.

Accelerating the greening and digital transformation of the energy industry to enhance energy efficiency is pivotal for constructing a new energy system. The high-quality development of the energy sector necessitates the support of emerging financial forces. This study utilizes panel data from 279 prefecture-level cities spanning from 2011 to 2021, employing mediation and moderation models to verify the synergistic impact of digital finance and green finance on energy efficiency. Findings indicate that the synergy between digital finance and green finance enhances energy efficiency. Mechanism analysis reveals that this synergy promotes energy efficiency through advancements in green and digital technology innovations. Climate policy uncertainty positively moderates the process by which digital finance and green finance synergistically improve energy efficiency, enhancing the intermediary effects of digital and green technologies. Environmental regulations similarly exert positive moderation on the joint impact of digital finance and green finance on energy efficiency, yet their effects vary heterogeneously, with market-based environmental regulatory tools demonstrating superior policy outcomes. Moreover, the impact of the synergy between digital finance and green finance on energy efficiency exhibits heterogeneity across geographic regions, development timelines, resource endowments, and policy trial effects.

Insect-electronics hybrid robots integrate live insects with small electronic backpacks. These backpacks guide insect movement and sense environmental data. Due to size and payload constraints, high-capacity batteries are impractical for prolonged energy supply. This study proposes a self-sustaining wireless sensing and flight control device with an energy management module and a Bluetooth slave module. This setup enables solar energy harvesting, wireless flight control of beetles, and the acquisition of image and attitude information. The device achieves directional flight control with a 72.5% success rate in turning. Operation duration increases by 46.6% in image-only mode and 50.9% in combined image and attitude angle mode under 20 000 lux indoor illuminance. Outdoor experiments demonstrate continuous operation at one image per second under favorable illuminance conditions, with a 92% increase in operation time when capturing images and yaw angles. This microelectronic device enhances the durability of insect robots during extended field missions, providing valuable insights into long-term environmental monitoring.

Abstract Energy information is vulnerable to malicious denial of service (DoS) attacks due to the diversity and openness of the smart grid environment. In order to cope with the above challenges, this paper first proposes to adopt Markov hopping model to describe the random packet loss of measurement due to DoS attacks. Then, based on Holt two‐parameter exponential smoothing and untraced Kalman filtering techniques, a one‐step predictive value compensation method for measurement data loss is proposed, and an improved dynamic untraced particle filtering algorithm based on data fusion compensation strategy is designed. Finally, an IEEE‐30 bus system is used to simulate the proposed dynamic state estimation method, which proves that the proposed method can effectively resist DoS attack.

Abstract Class IIa histone deacetylases (Class IIa HDACs) play critical roles in regulating essential cellular metabolism and inflammatory pathways. However, dissecting the specific roles of each class IIa HDAC isoform is hindered by the pan‐inhibitory effect of current inhibitors and a lack of tools to probe their functions beyond epigenetic regulation. In this study, a novel PROTAC‐based compound B4 is developed, which selectively targets and degrades HDAC7, resulting in the effective attenuation of a specific set of proinflammatory cytokines in both lipopolysaccharide (LPS)‐stimulated macrophages and a mouse model. By employing B4 as a molecular probe, evidence is found for a previously explored role of HDAC7 that surpasses its deacetylase function, suggesting broader implications in inflammatory processes. Mechanistic investigations reveal the critical involvement of HDAC7 in the Toll‐like receptor 4 (TLR4) signaling pathway by directly interacting with the TNF receptor‐associated factor 6 and TGFβ‐activated kinase 1 (TRAF6‐TAK1) complex, thereby initiating the activation of the downstream mitogen‐activated protein kinase/nuclear factor‐κB (MAPK/NF‐κB) signaling cascade and subsequent gene transcription. This study expands the insight into HDAC7's role within intricate inflammatory networks and highlights its therapeutic potential as a novel target for anti‐inflammatory treatments.

BackgroundIn this retrospective study, we aimed to identify key risk factors and establish an interpretable model for HCC with a diameter ≥ 5 cm using Lasso regression for effective risk stratification and clinical decision-making.MethodsIn this study, 843 patients with advanced hepatocellular carcinoma (HCC) and tumor diameter ≥ 5 cm were included. Using Lasso regression to screen multiple characteristic variables, cox proportional hazard regression and random survival forest models (RSF) were established. By comparing the area under the curve (AUC), the optimal model was selected. The model was visualized, and the order of interpretable importance was determined. Finally, risk stratification was established to identify patients at high risk.ResultLasso regression identified 8 factors as characteristic risk factors. Subsequent analysis revealed that the lasso-cox model had AUC values of 0.773, 0.758, and 0.799, while the lasso-RSF model had AUC values of 0.734, 0.695, and 0.741, respectively. Based on these results, the lasso-cox model was chosen as the superior model. Interpretability assessments using SHAP values indicated that the most significant characteristic risk factors, in descending order of importance, were tumor number, BCLC stage, alkaline phosphatase (ALP), ascites, albumin (ALB), and aspartate aminotransferase (AST). Additionally, through risk score stratification and subgroup analysis, it was observed that the median OS of the low-risk group was significantly better than that of the middle- and high-risk groups.ConclusionWe have developed an interpretable predictive model for middle and late HCC with tumor diameter ≥ 5 cm using lasso-cox regression analysis. This model demonstrates excellent prediction performance and can be utilized for risk stratification.

Due to significant anatomical variations in medical images across different cases, medical image segmentation is a highly challenging task. Convolutional neural networks have shown faster and more accurate performance in medical image segmentation. However, existing networks for medical image segmentation mostly rely on independent training of the model using data samples and loss functions, lacking interactive training and feedback mechanisms. This leads to a relatively singular training approach for the models, and furthermore, some networks can only perform segmentation for specific diseases. In this paper, we propose a causal relationship-based generative medical image segmentation model named GU-Net. We integrate a counterfactual attention mechanism combined with CBAM into the decoder of U-Net as a generative network, and then combine it with a GAN network where the discriminator is used for backpropagation. This enables alternate optimization and training between the generative network and discriminator, enhancing the expressive and learning capabilities of the network model to output prediction segmentation results closer to the ground truth. Additionally, the interaction and transmission of information help the network model capture richer feature representations, extract more accurate features, reduce overfitting, and improve model stability and robustness through feedback mechanisms. Experimental results demonstrate that our proposed GU-Net network achieves better segmentation performance not only in cases with abundant data samples and relatively simple segmentation targets or high contrast between the target and background regions but also in scenarios with limited data samples and challenging segmentation tasks. Comparing with existing U-Net networks with attention mechanisms, GU-Net consistently improves Dice scores by 1.19%, 2.93%, 5.01%, and 5.50% on ISIC 2016, ISIC 2017, ISIC 2018, and Gland Segmentation datasets, respectively.

Objective: Anxiety disorder (AD) is a common mental disorder related to cardiovascular disease morbidity. Oxidative stress plays a crucial role in the anxiety state and can lead to cardiac remodeling. Over-activation of the α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid receptor (AMPAR) in cardiomyocytes and neurons can cause oxidative stress. Additionally, the AMPAR inhibitor—2,3-dihydroxy-6-nitro-7-sulfamoyl-benzoquinoxaline-2,3-dione (NBQX) plays an important role in ameliorating oxidative stress. This study aimed to explore the anti-arrhythmic effects of NBQX in a rat model of anxiety. Methods: The AD model was induced using empty bottle stimulation. Male Sprague Dawley rats were randomly divided into four groups: control + saline, control + NBQX, AD + saline, and AD + NBQX. Open field test was conducted to measure anxiety-like behavior. Electrophysiological experiments, histological analysis, biochemical detection and molecular biology were performed to verify the effects of NBQX on the amelioration of electrical remodeling and structural remodeling. Furthermore, the nuclear factor erythroid 2-related factor 2 (Nrf2) inhibitor (ML385) was used in vitro to demonstrate the signaling pathway. Results: Oxidative stress levels increased with AMPAR over-activation in AD rats, leading to heightened vulnerability to ventricular fibrillation (VF). NBQX reverses anxiety and VF susceptibility. Our results showed that NBQX activated the Nrf2/heme oxygenase-1 (HO-1) pathway, leading to a decline in oxidative stress levels. Connexin 43 and ion channel expression was upregulated. NBQX treatment attenuated fibrosis and apoptosis. This effect was diminished by ML385 treatment in vitro. Conclusion: NBQX can alleviate VF susceptibility in rat models of anxiety by alleviating electrical remodeling, structural remodeling via regulating the Nrf2/HO-1 pathway to some extent.

BackgroundMany patients with constipation also suffer from varying degrees of malnutrition, and the relationship between the two conditions is a vicious cycle. Surgery is the final step in the treatment of constipation, with a success rate of up to 95%. This study aims to investigate the effects of surgical treatment on the nutritional status of patients with chronic constipation and malnutrition.MethodsA total of 60 patients with chronic constipation and various degrees of malnutrition who underwent surgery in our department from January 2020 to March 2023 were included in this study. Biochemical tests including BMI, albumin, total protein, hemoglobin, cholesterol and lymphocyte count were conducted, as well as measurements of inflammatory markers such as Interleukin-6 (IL-6), Interleukin-8 (IL-8), and C-reactive protein (CRP). Additionally, multiple nutritional risk screening scales (NRS2002, MUST, NRI, and MNA) and the prognostic nutritional index (PNI) were used to assess the nutritional status of patients before surgery, as well as at 1 month, 3 months, and 6 months post-surgery. Finally, we analyzed the factors influencing postoperative recovery outcomes in patients.ResultsCompared to pre-operation, the BMI of patients significantly increased at 1 month, 3 months, and 6 months after the operation, with statistically significant differences (p